metadata

base_model: google/pegasus-xsum
tags:
  - generated_from_trainer
metrics:
  - rouge
  - precision
  - recall
  - f1
model-index:
  - name: LLM_Teached_Pegasus_50k
    results: []

LLM_Teached_Pegasus_50k

This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.6796
Rouge1: 0.4613
Rouge2: 0.2127
Rougel: 0.3775
Rougelsum: 0.3772
Gen Len: 26.4655
Precision: 0.9092
Recall: 0.9073
F1: 0.9081

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	F1	Gen Len	Validation Loss	Precision	Recall	Rouge1	Rouge2	Rougel	Rougelsum
No log	1.0	390	0.9034	26.2967	1.8258	0.9049	0.9023	0.4338	0.1906	0.3496	0.3498
2.1621	2.0	781	0.9054	26.2727	1.7537	0.9068	0.9044	0.4449	0.2005	0.3633	0.3633
1.8794	3.0	1172	0.9066	26.4345	1.7268	0.9078	0.9058	0.4518	0.2061	0.3696	0.3695
1.8271	4.0	1560	0.9069	26.3971	1.7157	0.9082	0.906	0.4539	0.2075	0.3716	0.3714
1.8271	5.0	1951	0.9074	26.3015	1.7033	0.9087	0.9065	0.4561	0.2098	0.3735	0.3734
1.8067	6.0	2340	1.6897	0.4592	0.2114	0.3762	0.3759	26.4389	0.9089	0.9069	0.9077
1.7833	7.0	2731	1.6819	0.4598	0.2115	0.3764	0.376	26.3745	0.9092	0.9071	0.9079
1.7683	7.99	3120	1.6796	0.4613	0.2127	0.3775	0.3772	26.4655	0.9092	0.9073	0.9081

Framework versions

Transformers 4.36.0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.15.0